Files
ermnvldmr.com/services/docs/content/en/quetza/guides/deployment.md
T
deytenit b3638f4d63 fix: cyrillic fonts, dev certs, page head, and ru-text typography (#67)
🤖 PR generated for branch `fix/cyrillic-fonts-dev-certs-and-page-head`.

### Changes Summary
- **Fonts**: Add Cyrillic glyph subsets for Lato, EB Garamond, and Fira
Code.
- **Dev**: Support remote Root CA and encrypted dev CA key in
`.env.dev`.
- **UI & Kits**: Add size variant to `Breadcrumbs` component and enlarge
`PageHead` breadcrumbs with tuned collapse scroll threshold.
- **ESLint**: Add `no-hanging-particles` i18n & markdown typography rule
with auto-fixer.
- **Content & i18n**: Apply `ru-text` editorial and typography polish
(em dashes, number ranges, «ё» restoration, non-breaking spaces) across
`services/www` and `services/docs`.
2026-10-25 15:21:09 +03:00

1.9 KiB

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Deployment & Operations 2

Goal: Configure, deploy, and monitor a Quetza bot instance.

1. Environment Preparation

Quetza relies on environment variables for configuration. Never commit these to version control.

Variable Description Required
DISCORD_TOKEN Bot token from Discord Developer Portal Yes
CLIENT_ID Application ID for slash command registration Yes
LLAMA_API_KEY Required if using the AI module No 

2. Deployment Strategies

{{< tabs >}} {{< tab name="Docker (Recommended)" >}} Docker ensures a consistent runtime environment.

  1. Build the image:

    docker build -t quetza-bot .
    
  2. Run the container: bash docker run -d \ --env-file .env \ --name quetza \ quetza-bot {{< /tab >}} {{< tab name="Source" >}} Source deployment is useful for development.

  3. Install dependencies:

    pnpm install
    
  4. Build the project:

    pnpm build
    
  5. Start the bot: bash pnpm start {{< /tab >}} {{< /tabs >}}

3. Operational Monitoring

Once running, use these mechanisms to check health:

  • Logs: Check standard output (Docker logs) for initialization errors.
  • /ping Command: Verifies network latency and API responsiveness.
  • /modules Command: Lists all loaded modules to confirm feature availability.

Warning

Scaling Constraint: Quetza follows a single-instance-per-token model. Do not run multiple instances with the same token, as this will cause WebSocket conflicts.


See also: